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The present thesis aims to tackle two critical aspects of present and future cosmological analysis of Large-Scale Structure (LSS): accurate modelling of the nonlinear matter power spectrum beyond $\Lambda$CDM, and efficient computational…

Cosmology and Nongalactic Astrophysics · Physics 2025-08-15 Karim Carrion

The bispectrum is the leading non-Gaussian statistic in large-scale structure, carrying valuable information on cosmology that is complementary to the power spectrum. To access this information, we need to model the bispectrum in the weakly…

Cosmology and Nongalactic Astrophysics · Physics 2022-01-12 Tobias Baldauf , Mathias Garny , Petter Taule , Theo Steele

Cosmological perturbation theory is a powerful tool to predict the statistics of large-scale structure in the weakly non-linear regime, but even at 1-loop order it results in computationally expensive mode-coupling integrals. Here we…

Cosmology and Nongalactic Astrophysics · Physics 2017-02-17 Xiao Fang , Jonathan A. Blazek , Joseph E. McEwen , Christopher M. Hirata

We show that effective field theory techniques can be efficiently used to compute power corrections to the hard thermal loops (HTL) in a high temperature T expansion. To this aim, we use the recently proposed on-shell effective field theory…

High Energy Physics - Phenomenology · Physics 2017-11-27 Cristina Manuel , Joan Soto , Stephan Stetina

We present an \emph{Effective Static Approximation} (ESA) to the local field correction (LFC) of the electron gas that enables highly accurate calculations of electronic properties like the dynamic structure factor $S(q,\omega)$, the static…

Accurate predictions for the non-linear matter power spectrum are needed to confront theory with observations in current and near future weak lensing and galaxy clustering surveys. We propose a computationally cheap method to create an…

Cosmology and Nongalactic Astrophysics · Physics 2020-01-01 Hans Winther , Santiago Casas , Marco Baldi , Kazuya Koyama , Baojiu Li , Lucas Lombriser , Gong-Bo Zhao

Effective field theories (EFTs) provide an excellent framework for the search of heavy physics beyond the Standard Model, using the so-called bottom-up and top-down approaches. However, the vastness of possible UV scenarios makes the…

High Energy Physics - Phenomenology · Physics 2026-04-24 Guilherme Guedes , Pablo Olgoso

We formalize energy-scaling arguments in the Standard Model Effective Field Theory (SMEFT) to estimate effects of operators up to dimension ten. Introducing a classification based on the number of external legs and an energy-counting…

High Energy Physics - Phenomenology · Physics 2025-07-28 Benoît Assi , Adam Martin

We present a practical three-step procedure of using the Standard Model effective field theory (SM EFT) to connect ultraviolet (UV) models of new physics with weak scale precision observables. With this procedure, one can interpret…

High Energy Physics - Phenomenology · Physics 2015-07-10 Brian Henning , Xiaochuan Lu , Hitoshi Murayama

The virtues of an effective field theory (EFT) approach to many-body problems are illustrated by deriving the expansion for the energy of an homogeneous, interacting Fermi gas at low density and zero temperature. A renormalization scheme…

Nuclear Theory · Physics 2009-11-06 H. -W. Hammer , R. J. Furnstahl

$\tt DsixTools$ is a Mathematica package for the handling of the Standard Model Effective Field Theory (SMEFT) and the Low-energy Effective Field Theory (LEFT) with operators up to dimension six, both at the algebraic and numerical level.…

High Energy Physics - Phenomenology · Physics 2021-02-23 Javier Fuentes-Martin , Pedro Ruiz-Femenia , Avelino Vicente , Javier Virto

Long Short-Term Memory (LSTM) is one of the most widely used recurrent structures in sequence modeling. It aims to use gates to control information flow (e.g., whether to skip some information or not) in the recurrent computations, although…

Machine Learning · Computer Science 2018-06-11 Zhuohan Li , Di He , Fei Tian , Wei Chen , Tao Qin , Liwei Wang , Tie-Yan Liu

In order to constrain ultra light dark matter models with current and near future weak lensing surveys we need the predictions for the non-linear dark matter power-spectrum. This is commonly extracted from numerical simulations or from…

Cosmology and Nongalactic Astrophysics · Physics 2025-10-15 Dennis Fremstad , Hans A. Winther

Most of the upcoming cosmological information will come from analyzing the clustering of the Large Scale Structures (LSS) of the universe through LSS or CMB observations. It is therefore essential to be able to understand their behavior…

Cosmology and Nongalactic Astrophysics · Physics 2020-01-15 Tomohiro Fujita , Valentin Mauerhofer , Leonardo Senatore , Zvonimir Vlah , Raul Angulo

A logarithm transformation over the matter overdensity field $\delta$ brings information from the bispectrum and higher-order n-point functions to the power spectrum. We calculate the power spectrum for the log-transformed field $A$ at one,…

Cosmology and Nongalactic Astrophysics · Physics 2021-03-31 Henrique Rubira , Rodrigo Voivodic

In this work we extend our recently developed multi-fidelity emulation technique to the simulated Lyman-$\alpha$ forest flux power spectrum. Multi-fidelity emulation allows interpolation of simulation outputs between cosmological parameters…

Cosmology and Nongalactic Astrophysics · Physics 2022-10-25 M. A. Fernandez , Ming-Feng Ho , Simeon Bird

The bispectrum is the leading non-Gaussian statistic in Large-Scale Structure (LSS) clustering and encodes the interactions in the underlying field. It is thus an important diagnostic for primordial non-Gaussianity and higher order galaxy…

Cosmology and Nongalactic Astrophysics · Physics 2021-01-20 Theodore Steele , Tobias Baldauf

Large scale Density Functional Theory (DFT) based electronic structure calculations are highly time consuming and scale poorly with system size. While semi-empirical approximations to DFT result in a reduction in computational time versus…

Materials Science · Physics 2016-12-21 Ganesh Hegde , R. Chris Bowen

Recently, several algorithms for symbolic regression (SR) emerged which employ a form of multiple linear regression (LR) to produce generalized linear models. The use of LR allows the algorithms to create models with relatively small error…

Machine Learning · Computer Science 2017-03-13 Jan Žegklitz , Petr Pošík

Constraining the Epoch of Reionization (EoR) with physically motivated simulations is hampered by the high cost of conventional parameter inference. We present an efficient emulator-based framework that dramatically reduces this bottleneck…

Instrumentation and Methods for Astrophysics · Physics 2026-03-06 Saptarshi Sarkar , Tirthankar Roy Choudhury
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